Abstract:
The College Connection Score project is a web application developed using Python Flask, HTML, CSS, JavaScript, and Bootstrap technologies. It aims to provide students with a comprehensive platform for exploring higher education opportunities abroad, with a focus on colleges in the USA and UK.
The project utilizes datasets from K7 and other sources to facilitate the recommendation process. Key features of the platform include GRE preparation resources, student profile management, and a college search functionality based on the student's academic profile and preferences.
The GRE resources section offers curated PDFs and study materials to assist students in their exam preparation. During registration, students are prompted to input their personal details, including their first name, last name, contact number, email, password, and academic scores such as GRE, CGPA, TOEFL, and IELTS. GRE scores are mandatory, while other scores are optional but encouraged for better recommendations.
Upon logging in, students can edit their profiles and explore colleges in the USA and UK. The platform provides a dropdown menu to select different majors, such as Computer Science, MBA, Law, Nursing, and others.
The "Take me there" button redirects users to the login page if not logged in and displays college recommendations based on the chosen major and the student's academic profile if logged in. The project prioritizes user experience with intuitive navigation and user-friendly interfaces. It includes search functionalities to refine college searches based on criteria such as country, acceptance rate, and program specialization.
The platform aims to simplify the college search process and empower students to make informed decisions about their higher education journey. The College Connection Score project leverages technology and data-driven insights to connect students with relevant higher education opportunities and streamline the college exploration process.
1. Information Overload: International students face difficulty in navigating through the extensive information available on colleges and universities, making it challenging to identify institutions that align with their academic and personal preferences.
2. Lack of Personalization: Existing college search platforms often provide generic recommendations without considering the individual student's academic background, interests, and preferences.
3. Limited Access to Resources: Many students lack access to reliable resources for standardized test preparation, such as GRE materials, which are crucial for admission to international universities.
4. Complexity in Decision Making: The process of selecting colleges is complex, with factors such as program offerings, location, cost, and reputation needing to be considered simultaneously, making it overwhelming for students to make informed decisions.
5. Data Integration and Analysis: Integrating and analyzing diverse datasets, including academic scores, acceptance rates, and program details, pose technical challenges that need to be addressed for creating an effective recommendation system.
6. User Experience: The user interface and experience of existing college search platforms may not be intuitive or user-friendly, hindering students' ability to efficiently explore and compare different colleges.
7. Accessibility: Ensuring that the platform is accessible to students from diverse backgrounds, including those with disabilities and limited internet connectivity, is essential for providing equitable access to college resources.
By addressing these challenges, the College Connection Score project aims to streamline the college exploration process for international students, providing them with personalized recommendations and access to resources that facilitate informed decision-making in their higher education journey.
• Demo Video
• Complete project
• Full project report
• Source code
• Complete project support by online
• Life time access
• Execution Guidelines
• Immediate (Download)
Software Requirements:
1. Front-end:
• HTML
• CSS
• Bootstrap
• JavaScript
2. Back-end:
• Python
• Flask
• Datasets
• KNN
•CNN
3. Database:
•SQL lite
•DB browser
4. Vs Code
Hardware Requirements:
1. PC or Laptop
2. 500GB HDD with 4 GB above RAM
3. Keyboard and mouse
4. Basic Graphis card
1. Immediate Download Online
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